ee1e8abd87
* feat(tools): add seed/solution restore script * chore(curriculum): remove empty sections' markers * chore(curriculum): add seed + solution to Chinese * chore: remove old formatter * fix: update getChallenges parse translated challenges separately, without reference to the source * chore(curriculum): add dashedName to English * chore(curriculum): add dashedName to Chinese * refactor: remove unused challenge property 'name' * fix: relax dashedName requirement * fix: stray tag Remove stray `pre` tag from challenge file. Signed-off-by: nhcarrigan <nhcarrigan@gmail.com> Co-authored-by: nhcarrigan <nhcarrigan@gmail.com>
581 B
581 B
id, challengeType, videoId, dashedName
| id | challengeType | videoId | dashedName |
|---|---|---|---|
| 5e8f2f13c4cdbe86b5c72d95 | 11 | K8bz1bmOCTw | neural-networks-creating-a-model |
--question--
--text--
Fill in the blanks below to build a sequential model of dense layers:
model = __A__.__B__([
__A__.layers.Flatten(input_shape=(28, 28)),
__A__.layers.__C__(128, activation='relu'),
__A__.layers.__C__(10, activation='softmax')
])
--answers--
A: keras
B: Sequential
C: Dense
A: tf
B: Sequential
C: Categorical
A: keras
B: sequential
C: dense
--video-solution--
1